U.S. patent number 10,489,862 [Application Number 14/715,198] was granted by the patent office on 2019-11-26 for systems and methods for computing device protection.
This patent grant is currently assigned to LOOKOUT, INC.. The grantee listed for this patent is Lookout, Inc.. Invention is credited to Brian James Buck, John Gunther Hering, Kevin Mahaffey, William Neil Robinson.
United States Patent |
10,489,862 |
Hering , et al. |
November 26, 2019 |
Systems and methods for computing device protection
Abstract
Embodiments of the present disclosure help protect computing
devices by, among other things, identifying events that may pose a
risk to a computing device based on data from sensors coupled to
the computer device.
Inventors: |
Hering; John Gunther (San
Francisco, CA), Mahaffey; Kevin (San Francisco, CA),
Buck; Brian James (Livermore, CA), Robinson; William
Neil (Sunnyvale, CA) |
Applicant: |
Name |
City |
State |
Country |
Type |
Lookout, Inc. |
San Francisco |
CA |
US |
|
|
Assignee: |
LOOKOUT, INC. (San Francisco,
CA)
|
Family
ID: |
56297454 |
Appl.
No.: |
14/715,198 |
Filed: |
May 18, 2015 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20160343083 A1 |
Nov 24, 2016 |
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F
21/56 (20130101); G06F 21/50 (20130101); G06F
21/88 (20130101); G06Q 40/08 (20130101); H04M
1/72569 (20130101); G06F 2221/033 (20130101); G06F
2221/034 (20130101); G06F 2221/2111 (20130101); H04M
2250/12 (20130101) |
Current International
Class: |
G06Q
40/08 (20120101); G06F 21/50 (20130101); G06F
21/56 (20130101) |
Field of
Search: |
;705/4 |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
Weingart Steve H, Physical Security Devices for Computer
Sybsystems;, Springer-Verlag Berlin Heidelberg (Year: 2000). cited
by examiner .
GB Application No. 1608179.6, Combined Search and Examination
Report, dated Oct. 21, 2016. cited by applicant.
|
Primary Examiner: Ebersman; Bruce I
Assistant Examiner: Poe; Kevin T
Attorney, Agent or Firm: Greenberg Traurig, LLP
Claims
What is claimed is:
1. A computer-implemented method comprising: receiving sensor data
pertaining to a computing device from a plurality of sensors
coupled to the computing device, wherein the sensors include an
accelerometer and a gyroscope; obtaining data from the gyroscope,
the data indicating an extent of rotation of the computing device
during a period of free fall; identifying, based on the sensor
data, occurrence of an event posing a risk of damage to the
computing device, wherein identifying the event includes:
determining a plurality of computing devices having a
characteristic in common with the computing device, selecting a
threshold associated with a force of impact based on historical
data associated with screen damage for the plurality of computing
devices, wherein the historical data includes sensor data
associated with damage that is received from computing devices
other than the computing device, determining that the sensor data
for the computing device exceeds the threshold, determining, based
on data from the accelerometer, that the computing device
experiences deceleration, determining that the computing device is
dropped based on the period of free fall and the deceleration, and
determining based on the data from the accelerometer and the data
from the gyroscope that the computing device was accidentally
dropped; obtaining results of diagnostics for the computing device,
wherein the results of diagnostics include an image or video from a
camera of the computing device, the image or video including at
least a portion of a screen of the computing device, and wherein
the results of diagnostics further include diagnostics from a
diagnostics program operating on the computing device; identifying
a force of impact experienced by the computing device; identifying,
based on the results of the diagnostics and the identified force of
impact, damage or potential damage to the computing device;
transmitting, to a different computing device, an electronic
message including the sensor data for the computing device, the
results of the diagnostics, and identification information for the
computing device, wherein the different computing device is
configured to send a reply communication; in response to receiving
the reply communication, transmitting an electronic message to the
computing device regarding the event; and modifying, based on the
sensor data for the computing device, risk data for the plurality
of computing devices.
2. The method of claim 1, wherein the sensors further include a
thermal detector, and determining that the sensor data exceeds the
threshold includes determining that a temperature measured by the
thermal detector is below a first threshold or above a second
threshold.
3. The method of claim 1, wherein the sensors further include a
location detector and determining that the sensor data exceeds the
threshold includes determining that the computing device is within
a predetermined distance of another computing device.
4. The method of claim 1, wherein the sensors further include a
moisture sensor and determining that the sensor data exceeds the
threshold includes determining that a level of moisture measured by
the moisture detector exceeds a predetermined amount.
5. The method of claim 1, wherein the sensors further include an
altimeter and determining that the sensor data exceeds the
threshold includes determining that an altitude measured by the
altimeter exceeds a predetermined level.
6. The method of claim 1, wherein the sensors further include a
location detector and identifying occurrence of the event posing
the risk to the computing device further includes determining,
based on the data from the location detector, that the computing
device is in one or more of: an unexpected location, or a location
associated with an elevated risk of damage to the computing
device.
7. The method of claim 1, wherein identifying occurrence of the
event posing the risk to the computing device further includes
analyzing the sensor data for the computing device in conjunction
with previously-received sensor data for the computing device.
8. The method of claim 1, wherein identifying occurrence of the
event posing the risk to the computing device further includes
detecting malware on the computing device based on the results of
the diagnostics.
9. A non-transitory, computer-readable medium storing instructions
that, when executed by one or more computing devices, cause the one
or more computing devices to: receive sensor data pertaining to a
first computing device from a plurality of sensors coupled to the
first computing device, wherein the sensors include an
accelerometer and a gyroscope; obtain data from the gyroscope, the
data indicating an extent of rotation of the first computing device
during a period of free fall; identify, based on the sensor data
for the first computing device, occurrence of an event posing a
risk of damage to the first computing device, wherein identifying
the event includes: determining a plurality of computing devices
having a characteristic in common with the first computing device,
selecting a threshold associated with a force of impact based on
historical damage data for the plurality of computing devices,
wherein the historical damage data includes sensor data associated
with damage that is received from computing devices other than the
first computing device, determining that the sensor data for the
first computing device exceeds the threshold, determining, based on
data from the accelerometer, that the first computing device
experiences deceleration, determining that the first computing
device is dropped based on the period of free fall and the
deceleration, and determining based on the data from the
accelerometer and the data from the gyroscope that the first
computing device was accidentally dropped; obtain results of
diagnostics for the first computing device, wherein the results of
diagnostics include an image or video from a camera of the first
computing device, the image or video including at least a portion
of a screen of the first computing device, and wherein the results
of diagnostics further include diagnostics from a diagnostics
program operating on the first computing device; identify a force
of impact experienced by the first computing device; identify,
based on the results of the diagnostics and the identified force of
impact, damage or potential damage to the first computing device;
transmit, to a second computing device, an electronic message
including the sensor data for the first computing device, the
results of the diagnostics, and identification information for the
first computing device, wherein the second computing device is
configured to send a reply communication; in response to receiving
the reply communication, transmit an electronic message to the
first computing device regarding the event; and modify, based on
the sensor data for the first computing device, risk data for the
plurality of computing devices.
10. A system comprising: one or more computing devices; and memory
in communication with the one or more computing devices and storing
instructions that, when executed by the one or more computing
devices, cause the one or more computing devices to: receive sensor
data pertaining to a first computing device from a plurality of
sensors coupled to the first computing device, wherein the sensors
include an accelerometer and a gyroscope; obtain data from the
gyroscope, the data indicating an extent of rotation of the
computing device during a period of free fall; identify, based on
the sensor data for the first computing device, occurrence of an
event posing a risk of damage to the first computing device,
wherein identifying the event includes: determining a plurality of
computing devices having a characteristic in common with the first
computing device, selecting a threshold associated with a force of
impact based on historical damage data for the plurality of
computing devices, wherein the historical damage data includes
sensor data associated with damage that is received from computing
devices other than the first computing device, determining that the
sensor data for the first computing device exceeds the threshold,
determining, based on data from the accelerometer, that the first
computing device experiences deceleration, determining that the
first computing device is dropped based on the period of free fall
and the deceleration, and determining based on the data from the
accelerometer and the data from the gyroscope that the first
computing device was accidentally dropped; obtain results of
diagnostics for the first computing device, wherein the results of
diagnostics include an image or video from a camera of the first
computing device, the image or video including at least a portion
of a screen of the first computing device, and wherein the results
of diagnostics further include diagnostics from a diagnostics
program operating on the first computing device; identify a force
of impact experienced by the first computing device; identify,
based on the results of the diagnostics and the identified force of
impact, damage or potential damage to the first computing device;
transmit, to a second computing device, an electronic message
including the sensor data for the first computing device, the
results of the diagnostics, and identification information for the
first computing device, wherein the second computing device is
configured to send a reply communication; in response to receiving
the reply communication, transmit an electronic message to the
first computing device regarding the event; and modify, based on
the sensor data for the first computing device, risk data for the
plurality of computing devices.
Description
BACKGROUND
The use of computing devices has steadily increased as such devices
have become more capable. However, this rise in capability is often
accompanied by an increase in complexity and cost, such that the
damage or loss of a computing device (such as smartphones, tablets,
watches and other wearable computing devices, and/or laptop
computers). Additionally, computing devices are increasingly
portable, further exposing them to the risk that they may be
damaged (e.g., by being accidentally dropped) or lost (e.g., by
being misplaced or stolen).
Embodiments of the present disclosure help to address issues
related to protecting computing devices.
SUMMARY
Embodiments of the present disclosure help protect computing
devices by, among other things, identifying events that may pose a
risk to a computing device based on data from sensors coupled to
the computer device. A computer-implemented method according to
various aspects of the present disclosure includes: receiving data
pertaining to a computing device from a sensor coupled to the
computing device; identifying, based on the sensor data for the
computing device, an event posing a risk to the computing device,
wherein the risk comprises one or more of damage to the computing
device and loss of the computing device; and presenting, based on
the identified event, an offer to insure the computing device to a
user of the computing device.
The present disclosure includes various methods, apparatuses
(including computer systems) that perform such methods, and
computer readable media containing instructions that, when executed
by computing systems, cause the computing systems to perform such
methods.
Other features will be apparent from the accompanying drawings and
from the detailed description which follows.
BRIEF DESCRIPTION OF DRAWINGS
FIG. 1 is an exemplary process according to various aspects of the
present disclosure.
FIG. 2 is a block diagram of an exemplary system according to
various aspects of the present disclosure.
DETAILED DESCRIPTION
Subject matter will now be described more fully hereinafter with
reference to the accompanying drawings, which form a part hereof,
and which show, by way of illustration, specific example
embodiments. Subject matter may, however, be embodied in a variety
of different forms and, therefore, covered or claimed subject
matter is intended to be construed as not being limited to any
example embodiments set forth herein; example embodiments are
provided merely to be illustrative. Likewise, a reasonably broad
scope for claimed or covered subject matter is intended. Among
other things, for example, subject matter may be embodied as
methods, devices, components, or systems. Accordingly, embodiments
may, for example, take the form of hardware, software, firmware or
any combination thereof (other than software per se). The following
detailed description is, therefore, not intended to be taken in a
limiting sense.
In the accompanying drawings, some features may be exaggerated to
show details of particular components (and any size, material and
similar details shown in the figures are intended to be
illustrative and not restrictive). Therefore, specific structural
and functional details disclosed herein are not to be interpreted
as limiting, but merely as a representative basis for teaching one
skilled in the art to variously employ the disclosed
embodiments.
Reference in this specification to "one embodiment" or "an
embodiment" means that a particular feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment of the disclosure. The
appearances of the phrase "in one embodiment" in various places in
the specification are not necessarily all referring to the same
embodiment, nor are separate or alternative embodiments mutually
exclusive of other embodiments. Moreover, various features are
described which may be exhibited by some embodiments and not by
others. Similarly, various requirements are described which may be
requirements for some embodiments but not other embodiments.
Any combination and/or subset of the elements of the methods
depicted herein may be combined with each other, selectively
performed or not performed based on various conditions, repeated
any desired number of times, and practiced in any suitable order
and in conjunction with any suitable system, device, and/or
process. The methods described and depicted herein can be
implemented in any suitable manner, such as through software
operating on one or more computer systems. The software may
comprise computer-readable instructions stored in a tangible
computer-readable medium (such as the memory of a computer system)
and can be executed by one or more processors to perform the
methods of various embodiments.
FIG. 1 is an exemplary process according to aspects of the present
disclosure. In this example, method 100 includes receiving data
from a sensor coupled to a computing device (110), identifying an
event posing a risk to the computing device based on the sensor
data (120), presenting an offer to insure the computing device to a
user of the computing device (130), and modifying risk data based
on the received sensor data (140). The steps of method 100 may be
performed (in whole, in part, and/or in conjunction with other
steps) using any combination of computing devices, such as the
server computing device 210 and client computing device 220
depicted in FIG. 2.
The sensor data may be received (110) by any number of different
systems, devices, and/or software applications. In one exemplary
embodiment, data is received from a sensor coupled to a computing
device by a software application running on the computing device.
In this example, the software application operating on the
computing device could also perform steps 120-140 of method 100,
alone or in conjunction with another device.
The sensor data may pertain to any type of computing device, such
as a smartphone, a laptop computer, a desktop computer, a mobile
subscriber communication device, a wearable computing device, a
personal digital assistant (PDA), a tablet computer, an electronic
book or book reader, a digital camera, a video camera, a video game
console, and/or any other suitable computing device.
Data may be received (110) from any number and type of different
sensors, and any number of different events posing a risk may be
identified (120) using the sensor data. For example, an event
posing a risk may be identified (120) based on determining that
data from one or more sensors exceeds a predetermined threshold.
Any desired thresholds can be utilized, including thresholds
provided by third parties (such as an insurance provider associated
with the offer to insure the computing device that is presented to
the user) as well as thresholds that are selected based on risk
data for other computing devices, such as devices that have one or
more characteristics in common with the computing device the sensor
data pertains to. As used herein, a "common characteristic" refers
to any feature that is the same or similar to a feature of another
computing device for purposes of evaluating a risk, but such
characteristics need not be identical. In some exemplary
embodiments, the sensor data may include data from a thermal
detector, and an event posing a risk to the computing device may be
identified in response to a temperature measured from the thermal
detector that is below a first threshold (e.g., too cold) or above
a second threshold (e.g., too hot).
Risks identified by the embodiments of the present disclosure may
include any event posing any sort of risk to the device. For
example, an event may be identified as posing a risk to a computing
device where the event could cause damage to the computing device.
Such damage may include, for example, the complete or partial or
degradation destruction of a component and/or function of the
device, physical damage (e.g., a cracked display screen), damage to
a software component (e.g., an application is rendered at least
partially inoperable, data is lost or stolen, etc.), cosmetic
damage (e.g., a scratch or dent in the casing of the device that
may or may not affect its functionality), and/or economic damage
(e.g., the device is worth less after the event than before the
event). Damage to the computing device may also include the
computing device running slower than normal, being unable to access
all of the files in memory, being unable to decrypt some files,
being unable to remove a file from memory, and/or having corrupted
file content which degrades the functionality of the computing
device. An event may also pose a risk to the device where it may
involve the loss of the device, such as due to the device being
misplaced or stolen.
In some embodiments, data may be received from a moisture detector,
and an event posing a risk to the computing device may be
identified in response to the moisture detector measuring a level
of moisture that exceeds a predetermined threshold. Data may also
be received from an altimeter, and an event posing a risk to the
computing device identified in response to the altitude (or
elevation) of the computing device exceeding a predetermined height
or depth.
In other exemplary embodiments, sensor data may be received from a
location detector that provides the location of the mobile device.
In some embodiments, the location detector may include a global
positioning system (GPS) embedded within a computing device. In
addition, or in the alternative, the location detector may comprise
software or hardware that analyzes the network(s) to which the
computing device is connected and/or in communication with the
computing device and, based on the strength of the connection to
such networks, determine the location of the computing device. For
example, in cases where a computing device connected to, or in
communication with, a cellular network, the cellular base stations
(and their locations) in communication with the computing device
may be used to identify which cell the computing device is located.
Likewise, the location of wireless access points connected to a
computing device (and the strength of such connections) can be used
to identify the location of the computing device. Furthermore,
location data for the computing device from multiple sources may be
analyzed to help improve the accuracy of the location
determination.
In embodiments utilizing data from one or more location detectors
an event that poses a potential risk to the computing device may be
identified in response to determining that the computing device is
in an unexpected location. For example, embodiments of the present
disclosure may analyze the history of locations of the computing
device and identify a potential risk to the computing device in
response to determining that the computing device is unexpectedly
outside a predetermined distance from the locations the computing
device is typically found. In this example, determining that the
computing device is in an unexpected location may be indicative
that the user of the computing device is travelling, in which case
the user may wish to insure the computing device against damage or
loss (including theft) while travelling.
Location information for the computing device may also be used to
determine that the computing device is in a location associated
with an elevated risk of loss and/or damage to the device. For
example, embodiments of the present disclosure may identify a risk
to the computing device in response to determining that the
computing device is located in a transit hub (such as an airport or
subway) and that the transit hub is, based on data collected for
other devices having one or more characteristics in common with the
computing device from to which the location information pertains,
associated with an elevated risk of theft of the computing device.
Similarly, the location information may be used to determine that
the computing device is at an elevated risk of damage, such as in
cases where the mobile device is located near a body of water,
rough terrain (such as a ski slope), and/or elevated terrain (such
as a mountain trail).
In some exemplary embodiments, location information from a location
detector can be used to identify dynamic threats to the computing
device. For example, location information for the computing device
can be compared against weather information to identify conditions
(e.g., rain, an electrical storm, etc.) that may pose a risk to the
computing device. Similarly, the present location of the computing
device can be compared against the locations of computing devices
associated with individuals related to the theft of computing
devices determined, for example, based on publically-available
court records.
The sensor data may further be received from one or more inertial
sensors, such as one or more accelerometers, gyroscopes, and/or
magnetometers (e.g., compasses). Inertial sensors may be used
(alone or in conjunction with each other) as location detectors.
Additionally, such sensors may be used to identify events posing a
risk to the computing device, such as determining, based on data
from an accelerometer, that the computing device experiences a
rapid deceleration. Further, embodiments of the present disclosure
can identify that the computing device has been dropped based on,
for example, a period of free fall measured by the accelerometer
followed by the measuring of the rapid deceleration.
Data from the inertial sensor(s) may also be used to identify the
force of impact experienced by the computing device. Such data may
be used in conjunction with other information, such as the results
of a diagnostics program operating on the computing device, to help
specifically identify damage (or potential damage) to the computing
device. Additionally, embodiments of the present disclosure may
determine whether data from the accelerometer or other sensors is
indicative of the computing device being accidentally dropped or
intentionally thrown.
For example, in cases where data from an accelerometer coupled to
the computing device shows the computing device experienced an
acceleration consistent with normal gravity, and data from a
gyroscope coupled to the computing device indicates the computing
device experienced little or no rotation before impact, then a
determination may be made that the computing device was likely
dropped accidentally. In a contrasting example, where the data from
the accelerometer indicates an acceleration significantly higher
than normal gravity, and the gyroscope measures multiple rotations
of the computing device before impact, a determination may be made
that the computing device was likely intentionally thrown.
Thresholds for the sensor data may be selected such that an event
posing a risk is identified before actual harm is done to the
device. For example, in embodiments where data from a thermal
detector is received, the upper threshold (e.g., for excessive
heat) or the lower threshold (e.g., for excessive cold) could be
selected such that the offer for insurance is presented to the user
of the computing device (130) before temperatures reach an extreme
in either case that is likely to harm the computing device. Among
other things, presenting the offer for insurance (130) prior to any
actual damage occurring to the mobile device serves to warn the
user of the computing device of potentially harmful situations
(allowing the user the to correct the situation) and provides the
offer early enough that the offer isn't being extended to a device
that is already damaged, thus helping to protect the insurer from
excessive claims.
Events posing a risk to the computing device may be identified
(120) using data from one sensor or from multiple sensors. For
example, data from multiple sensors may be used to determine that a
mobile device (or user thereof) is engaged in a situation or
activity that poses a risk to the device. In one embodiment, for
example, data from a location detector coupled to the computing
device may be used to determine that the computing device is near,
in, or on, a body of water, while data from a moisture sensor
coupled to the computing device is used to determine that the
device is being exposed to an excessive level of moisture. The
combination of the data from the two sensors may thus be used to
determine that the user is likely swimming or boating with the
computing device on his/her person.
In another example, data from an altimeter coupled to a computing
device may indicate that a computing device is at an excessively
high altitude, while a thermal detector indicates an excessively
low temperature, a moisture detector detects moisture consistent
with fog or clouds, and a location detector indicates the user is
located on a mountain. In this example, the combination of sensor
data may be used to determine that he user is mountain climbing
and/or hiking, and that the computing device may be at risk of
being dropped from an excessive height or subjected to inclement
weather conditions.
Events posing a risk to the computing device may be identified
(120) based on other information in addition, or in the
alternative, to the sensor data. For example, an event posing a
risk to the computing device may be identified in response to virus
protection software (or another system or software application)
detecting the presence of malware on the computing device. An offer
for insurance may be directed not only to the identified event
(e.g., a potential loss and/or theft of data from the malware) but
also to other related (e.g., identity theft protection insurance)
or unrelated (e.g., protection for breakage of the display screen)
coverage.
Events posing a risk to a computing device may also be identified
based on the expiration of an insurance policy for a computing
device, the initiation of a "device locate" operation by the user
of the device or another entity, the elapsing of a predetermined
period of time from one or more of the: purchase of the device,
activation of the device, and installation of a software
application on the device.
In another example, events posing a risk to the computing device
may be identified (120) based on a history of identified events
(and/or received sensor data) for the computing device, as well as
based on risk data pertaining to other computing devices. In this
context, "risk data" refers to any data that may be used to
determine a probability that a particular computing device will
experience damage and/or loss base on one or more identified
events.
For example, consider a particular computing device ("Device A")
that is determined to have been dropped based on data received from
inertial sensors coupled to Device A as discussed above. In this
example, Device A is determined to have been dropped six times
prior to the latest identified drop (i.e., the seventh drop) based
on previously-received sensor data. Risk data for a plurality of
other computing devices having one or more characteristics in
common with Device A (e.g., common manufacturer, weight,
dimensions, screen thickness or other components features, etc.)
may be analyzed and a determination made that the glass in the
display screen of Device A has a 20% probability of cracking with
every drop before the tenth drop, but a 70% probability of cracking
with every drop after and including the tenth drop.
Based on the risk data for the other computing devices, embodiments
of the present disclosure may select a threshold of seven drops to
present (130) an offer for insuring the computing device against
damage to the display screen (as well as other events), thus
allowing the user to insure the device before the device is likely
to be damaged. The threshold may also be provided by an insurer
associated with the offer for insurance. In this manner,
embodiments of the present disclosure can use historical data from
a computing device and historical data from other related devices
to determine specific risk probabilities and identify appropriate
thresholds for offering insurance for the computing device. This
not only helps provides a benefit to the user of the computing
device before the computing device is damaged, but helps insurers
distribute such offers while such computing devices are still in
good working order.
Embodiments of the present disclosure may be used to offer
insurance policies to groups of computing devices associated with a
particular, user, organization, and/or system of networked devices.
In such cases, an event identified for one computing device in a
collection may trigger offers for insurance on one or more other
devices in the collection, regardless of whether such devices
experienced the event. In this manner, embodiments of the present
disclosure can simultaneously offer insurance coverage to a
collection of computing devices without necessitating prior
intervention from users or administrators of the collection.
In a collection of devices, the identified event posing a risk to a
device may include the identification of one or more uninsured
devices in a collection of devices. The identified event may also
be identified in response to determining that a new device is added
to a collection, determining that the number of devices in a
collection has met or exceeded a predetermined threshold,
identifying a hardware or software failure on a device in the
collection, as well as to determining that a device associated with
a group of devices has not been detected for at least a
predetermined period of time. In the latter case, the absence of a
device may be indicative of the device being lost or damaged. In
each case, an offer to insure one or more devices in the collection
may be presented (130). Such offers may apply only to uninsured
devices or add/modify coverage to existing policies.
Embodiments of the present disclosure can also help provide
complete coverage to collections of devices associated with
different entities. For example, it is common within many business
organizations for there to be a mixture of devices connected to the
organization's network that are owned/licensed by the organization
itself or owned by individual employees/members of the
organization. For example, a particular employee ("Employee A") may
be issued a desktop computer and laptop computer by his company,
but also uses his smartphone and tablet computer to connect to the
company's network, access files and email, etc. Employee A's use of
the smartphone and tablet computer are commonly referred to as
policies known as "bring your own device" (BYOD) or "bring your own
technology" (BYOT). In cases, where organizations permit BYOD/BYOT,
embodiments of the present disclosure can identify each of the four
devices as being part of the organization's collection of devices,
and provide insurance offers to some or all of the individual
devices in the collection in response to various events identified
as posing a risk to a particular device and/or the entire
collection and based on preferences of the organization, members of
the organization, and insurance providers.
For example, an offer for insurance for a collection of devices may
be presented (130) in response to a variety of events, including
the number of BYOD/BYOT devices meeting or exceeding a
predetermined threshold, the status of a member within the
organization changing, the addition or departure of a member of the
organization, the detection of an enterprise-level cyber security
event, as well as other events discussed herein.
Insurance policies offered for devices in a collection may be
customized based on the type of device, the user(s) associated with
the device, the location of the device, and other factors. Such
coverage may be offered for mobile devices that can be easily
removed from an organization's premises and/or used for multiple
purposes outside of those of the organization. For example, an
insurance policy might cover a particular device during its use in
work-related conditions, but not during its use for personal
reasons.
In such cases, embodiments of the present disclosure may utilize
the sensor(s) coupled to the computing device and other hardware or
software components to monitor the usage of the device to help
determine the manner in which the device is used at the time the
device is lost or damaged to help resolve the resulting insurance
claim. For example, a location detector (e.g., as described above)
may be used to identify when the device is at a work location,
within a predetermined distance of a work location, accompanying a
user of the device on work/business trips, accompanying user while
the user is working from home (i.e., telecommuting), accompanying
the user while the user is travelling for personal reasons, and
other events. In this manner, embodiments of the disclosure can
provide customized insurance offers to organizations that cover
specific uses of a mobile device and exclude others to help reduce
the overall costs of insuring the devices used in the organization.
Additionally, some embodiments may provide separate offers to the
device user to cover personal usage of a device where the user's
organization does not cover such use. Such separate offers may be
provided at the same cost as offered to the organization, thus
allowing the user to benefit from bulk insurance purchases by the
organization.
Embodiments of the present disclosure may present (130) an offer to
insure a computing device that provides any desired coverage, and
which may be based on any desired criteria. For example, an offer
for insurance of a computing device may selectively provide
coverage based on the age of the device, type of the device and/or
its components, events identified (or not identified) for the
device, an event associated with a user of the computing device
(whether or not it occurs on a particular device), an organization
associated with the computing device and/or to which the user
belongs, as well as other factors.
For example, presentation of an offer to insure a computing device
(130) may include determining that the user does not have an
existing insurance policy covering the computing device to avoid
duplicate coverage. Such a determination may be performed by
retrieving policy information from a database, communicating with a
service provider associated with the computing device, and/or by
retrieving information from an insurance exchange or provider.
Presentation of the offer (130) may also include identifying a
number of insurance claims made by the user within a predetermined
period of time, results of diagnostics run on the computing device
(e.g., to assess the health of the device), as well as analyzing
the repair history of the computing device.
In some embodiments, the offer to insure a computing device may be
generated by the same entity (e.g., an insurance provider) that
provides the system for receiving the sensor data (110),
identifying the event posing a risk to the computing device (120)
or other functionality related to the present disclosure. In other
embodiments, the offer to insure a computing device may be received
from, or generated in behalf of, a third party insurer. In such
cases, presenting the offer for insuring the computing device (130)
may include transmitting the sensor data received from the
computing device (and/or information describing the identified
event posing a risk to the computing device) to the insurance
provider. Information identifying the user of the computing device
may also be provided to the insurance provider. The insurance
provider may then respond with an approval or disapproval to
provide the offer to insure the computing device. Such
communication may occur between computing devices in communication
with each other via a network, such as network 230 shown in FIG. 2
and described in more detail below.
The offer to insure a computing device may be presented (130) to a
user in any suitable manner. In some embodiments, for example, the
offer may be presented (130) via an electronic message to the user
via email, short message service (SMS), multimedia messaging
service (MMS), transmission control protocol/Internet protocol
(TCP/IP) networking protocols, and/or using any other desired
message format and communication protocol. Such messages may
include text, data, a hyperlink to a website, and other
information.
The offer to insure the computing device may also be provided
directly to the computing device via a display window. The offer to
insure a computing device may be encrypted and/or require
verification/validation of the user by the computing device to
access the offer. For example, a user may be required to enter a
password, personal identification number (PIN), swipe pattern,
biometric (e.g., fingerprint scan), or other validation before
receiving the offer for insurance. Such validation may be
presented, for example, by unlocking the display screen of the
computing device or separate/additional validation may be required
from the user to receive the offer.
In some embodiments, information on the health/status of the
computing device may be provided to an insurance provider as part
of generating the offer, presenting the offer, and/or as a
condition of acceptance of the offer by the user of the computing
device. In some embodiments, such information may be automatically
retrieved from the computing device using diagnostic software
operating on the device or another system in communication with the
device. Additionally, such diagnostic information may be retrieved
subsequent to the acceptance of the insurance offer to help monitor
the status of the device and identify events that may trigger the
insurance policy associated with the device.
In some exemplary embodiments, the user is instructed to take a
picture of a mobile computing device in a mirror using a camera
mounted in the device that faces in same direction as the display
screen (i.e., a front-facing camera). In this example, a software
application on the mobile device displays a picture or pattern on
the screen of mobile device as the user takes the picture. The
application captures the image, which is used to determine that the
display is operative and not cracked. The user may also be required
to take images of the sides and/or back of the device via the
mirror (e.g., using a back-facing camera) to verify the body,
ports, and other portions of the device are not damaged. The user
may also (or alternatively) be instructed to take a video of the
camera. By capturing the image/video directly from the camera by
the software application, embodiments of the present disclosure
help ensure that the images are not tampered with. Such
images/video can also be used to diagnose issues with the
camera(s), such as cracked lenses and the like.
The sensor data received from the computing device may be used to
modify risk data (140) collected for a group of computing devices
having one or more characteristics in common with the device
providing the sensor data. As described above, risk data for a
plurality of computing devices having one or more characteristics
in common with a device from which sensor data is received can be
used to identify events posing a risk to the device. As sensor data
and/or information regarding identified events is collected over
time, such information may be used to modify the existing risk
data, thereby providing a statistically better collection of data
upon which to identify future risk events.
As described previously, the functionality of embodiments of the
present disclosure may be implemented using any number of different
computing devices. In one exemplary embodiment, a server generates
updated risk data associated with a population of mobile devices
based on the data associated with the detection of an event from a
computing device as well as data received from other computing
devices having at least one characteristic in common (i.e., the
same or similar for purposes of evaluating risk) with the mobile
device. The updated/modified risk data is then used in identifying
future events that may pose a risk to computing devices.
FIG. 2 is a block diagram of system which may be used in
conjunction with various embodiments. While FIG. 2 illustrates
various components of a computer system, it is not intended to
represent any particular architecture or manner of interconnecting
the components. Other systems that have fewer or more components
may also be used.
In FIG. 2, system 200 includes a server computing device 210
comprising a processor 212, memory 214, and user interface 216.
Server 210 may include any number of different processors, memory
components, and user interface components, and may interact with
any other desired systems and devices in conjunction with
embodiments of the present disclosure. Client computing device 220
may likewise include similar components.
The functionality of the server 210 and/or client 220, including
the steps of the methods described above (in whole or in part), may
be implemented through the processor(s) of the respective system
(e.g., processor 212) executing computer-readable instructions
stored in the memory (e.g. memory 214). The memory of the server
210 and/or client 220 may store any computer-readable instructions
and data, including software applications, applets, and embedded
operating code. Any combination of the functionality of the methods
described herein may be performed via software operating on the
server 210 and/or client 220.
The functionality of the system 210 or other system and devices
operating in conjunction with embodiments of the present disclosure
may also be implemented through various hardware components storing
machine-readable instructions, such as application-specific
integrated circuits (ASICs), field-programmable gate arrays (FPGAs)
and/or complex programmable logic devices (CPLDs). Systems
according to aspects of certain embodiments may operate in
conjunction with any desired combination of software and/or
hardware components.
In the server 210, for example, the processor 212 retrieves and
executes instructions stored in the memory 214 to control the
operation of the system 210. Any type of processor, such as an
integrated circuit microprocessor, microcontroller, and/or digital
signal processor (DSP), can be used in conjunction with embodiments
of the present disclosure. A memory 214 operating in conjunction
with embodiments of the disclosure may include any combination of
different memory storage devices, such as hard drives, random
access memory (RAM), read only memory (ROM), FLASH memory, or any
other type of volatile and/or nonvolatile memory. Data can be
stored in the memory 214 in any desired manner, such as in a
relational database.
The server 210 and/or client 220 may include a user interface
(e.g., user interface 216) that may include any number of input
devices (not shown) to receive commands, data, and other suitable
input. The user interface of the server 210 and/or client 220 may
also include any number of output devices (not shown) to provides
the user with data, notifications, and other information. Typical
I/O devices may include mice, keyboards, modems, network
interfaces, printers, scanners, video cameras and other
devices.
The server 210 and client 220 may communicate with any number of
other systems and devices in any desired manner, including via
network 230. The server 210 and/or client 220 may be, include, or
operate in conjunction with, a laptop computer, a desktop computer,
a mobile subscriber communication device, a smartphone, a personal
digital assistant (PDA), a tablet computer, a wearable computing
device, an electronic book or book reader, a digital camera, a
video camera, a video game console, and/or any other computing
device.
The network 230 may include any electronic communications system or
method. Communication among components operating in conjunction
with embodiments of the present disclosure may be performed using
any suitable communication method, such as, for example, a
telephone network, an extranet, an intranet, the Internet, point of
interaction device (point of sale device, personal digital
assistant (e.g., iPhone.RTM., Palm Pilot.RTM., Blackberry.RTM.),
cellular phone, kiosk, etc.), online communications, satellite
communications, off-line communications, wireless communications,
transponder communications, local area network (LAN), wide area
network (WAN), virtual private network (VPN), networked or linked
devices, keyboard, mouse and/or any suitable communication or data
input modality. Systems and devices of the present disclosure may
utilize TCP/IP communications protocols as well as IPX, Appletalk,
IP-6, NetBIOS, OSI, any tunneling protocol (e.g. IPsec, SSH), or
any number of existing or future protocols.
The term "non-transitory" is to be understood to remove only
propagating transitory signals per se from the claim scope and does
not relinquish rights to all standard computer-readable media that
are not only propagating transitory signals per se. Stated another
way, the meaning of the term "non-transitory computer-readable
medium" should be construed to exclude only those types of
transitory computer-readable media which were found in In Re
Nuijten to fall outside the scope of patentable subject matter
under 35 U.S.C. .sctn. 101.
No claim element herein is to be construed under the provisions of
35 U.S.C. 112, sixth paragraph, unless the element is expressly
recited using the phrase "means for." As used herein, the terms
"comprises", "comprising", or any other variation thereof, are
intended to cover a non-exclusive inclusion, such that a process,
method, article, or apparatus that comprises a list of elements
does not include only those elements but may include other elements
not expressly listed or inherent to such process, method, article,
or apparatus.
Where a phrase similar to "at least one of A, B, or C," "at least
one of A, B, and C," "one or more A, B, or C," or "one or more of
A, B, and C" is used, it is intended that the phrase be interpreted
to mean that A alone may be present in an embodiment, B alone may
be present in an embodiment, C alone may be present in an
embodiment, or that any combination of the elements A, B and C may
be present in a single embodiment; for example, A and B, A and C, B
and C, or A and B and C.
Changes and modifications may be made to the disclosed embodiments
without departing from the scope of the present disclosure. These
and other changes or modifications are intended to be included
within the scope of the present disclosure, as expressed in the
following claims.
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